Using Big Data In A Crisis: Nepal Earthquake

As I write this, hundreds of emergency services, charities, disaster relief agencies and volunteers are doing their best to help people affected by the terrible Nepalese earthquake which struck during the weekend. And Big Data is playing its part, too – with crowdsourced, data-driven efforts to connect people outside the country with their missing loved ones, and assist in getting aid to where it is needed.

Big Data is the name given to our ever-increasing ability to collect more data from a multitude of sources, and analyze it for insights using advanced computer algorithms. Patterns humans can't see provide a better understanding of situations and solutions to problems. Disasters are big, messy and noisy situations, and exactly the sort of conditions in which Big Data can help to make sense of the chaos. The massive amounts of data that we are generating with mobile phones, satellites and social media can all play a part in providing clues to the best way to respond to a situation.

Much of the work on developing Big Data systems to help with disaster relief began in the wake of the 2010 Haiti earthquake and the 2011 Tohuku, Japan earthquake and tsunami. Japan and the US instigated a joint research program to find workable methods of using data to ease the toll of natural disasters which kill thousands each year, and cost the global economy billions. Last year, the US National Science Foundation and Japanese Science and Technology Agency offered $2 million in funding to groups working on data-driven solutions to disaster management problems.

At the other end of the scale, crowdsourced, data-led initiatives have also started off at a grassroots level, with community members coming together to collate data to assist others. This happened following Hurricane Sandy in the US, when high school students collaborated to create an online map of the New York and New Jersey area showing where gas was available. Following Typhoon Haiyan in the Philippines, the international Red Cross collaborated with volunteers around the world to map the effects on the region and its people. One spokesman said “Online volunteering platforms scale very well … before there would be one or two people pouring over satellite imagery. Now there’s 700 volunteers”.

The four key elements of disaster management are prevention, preparation, response and recovery. Big Data has potential to help with all of them.

While not much can be done to prevent natural disasters, sophisticated Big Data systems such as those developed by Palantir are being used to crack down on man-made disasters such as those caused by terrorism. But when it comes to “acts of God”, of course the focus will be on preparation, response and recovery.

Companies such as Terra Seismic carry out real-time monitoring of satellite data and environmental factors which they say allow them to predict earthquakes anywhere in the world with 90% accuracy. Being pre-warned will make carrying out the next two stages of disaster-management – response and recovery – far simpler.